Anuj Mubayi

Climate change and influenza: the likelihood of early and severe influenza seasons following warmer than average winters.

The 2012-13 influenza season had an unusually early and severe start in the US, succeeding the record mild 2011-12 influenza season, which occurred during the fourth warmest winter on record. Our analysis of climate and past US influenza epidemic seasons between 1997-98 to present indicates that warm winters tend to be followed by severe epidemics with early onset, and that these patterns are seen for both influenza A and B. We posit that fewer people are infected with influenza during warm winters, thereby leaving an unnaturally large fraction of susceptible individuals in the population going into the next season, which can lead to early and severe epidemics. In the event of continued global warming, warm winters such as that of 2011-12 are expected to occur more frequently. Our results thus suggest that expedited manufacture and distribution of influenza vaccines after mild winters has the potential to mitigate the severity of future influenza epidemics.

Estimate of the reproduction number of the 2015 Zika virus outbreak in Barranquilla, Colombia, and estimation of the relative role of sexual transmission

BACKGROUND In 2015, the Zika arbovirus (ZIKV) began circulating in the Americas, rapidly expanding its global geographic range in explosive outbreaks. Unusual among mosquito-borne diseases, ZIKV has been shown to also be sexually transmitted, although sustained autochthonous transmission due to sexual transmission alone has not been observed, indicating the reproduction number (R0) for sexual transmission alone is less than 1. Critical to the assessment of outbreak risk, estimation of the potential attack rates, and assessment of control measures, are estimates of the basic reproduction number, R0. METHODS We estimated the R0 of the 2015 ZIKV outbreak in Barranquilla, Colombia, through an analysis of the exponential rise in clinically identified ZIKV cases (n=359 to the end of November, 2015). FINDINGS The rate of exponential rise in cases was ρ=0.076days-1, with 95% CI [0.066,0.087] days-1. We used a vector-borne disease model with additional direct transmission to estimate the R0; assuming the R0 of sexual transmission alone is less than 1, we estimated the total R0=3.8 [2.4,5.6], and that the fraction of cases due to sexual transmission was 0.23 [0.01,0.47] with 95% confidence. INTERPRETATION This is among the first estimates of R0 for a ZIKV outbreak in the Americas, and also among the first quantifications of the relative impact of sexual transmission.

Contagion in mass killings and school shootings

Background Several past studies have found that media reports of suicides and homicides appear to subsequently increase the incidence of similar events in the community, apparently due to the coverage planting the seeds of ideation in at-risk individuals to commit similar acts. Methods Here we explore whether or not contagion is evident in more high-profile incidents, such as school shootings and mass killings (incidents with four or more people killed). We fit a contagion model to recent data sets related to such incidents in the US, with terms that take into account the fact that a school shooting or mass murder may temporarily increase the probability of a similar event in the immediate future, by assuming an exponential decay in contagiousness after an event. Conclusions We find significant evidence that mass killings involving firearms are incented by similar events in the immediate past. On average, this temporary increase in probability lasts 13 days, and each incident incites at least 0.30 new incidents (p = 0.0015). We also find significant evidence of contagion in school shootings, for which an incident is contagious for an average of 13 days, and incites an average of at least 0.22 new incidents (p = 0.0001). All p-values are assessed based on a likelihood ratio test comparing the likelihood of a contagion model to that of a null model with no contagion. On average, mass killings involving firearms occur approximately every two weeks in the US, while school shootings occur on average monthly. We find that state prevalence of firearm ownership is significantly associated with the state incidence of mass killings with firearms, school shootings, and mass shootings.

Comparing vector–host and SIR models for dengue transmission.

Various simple mathematical models have been used to investigate dengue transmission. Some of these models explicitly model the mosquito population, while others model the mosquitoes implicitly in the transmission term. We study the impact of modeling assumptions on the dynamics of dengue in Thailand by fitting dengue hemorrhagic fever (DHF) data to simple vector-host and SIR models using Bayesian Markov chain Monte Carlo estimation. The parameter estimates obtained for both models were consistent with previous studies. Most importantly, model selection found that the SIR model was substantially better than the vector-host model for the DHF data from Thailand. Therefore, explicitly incorporating the mosquito population may not be necessary in modeling dengue transmission for some populations.

A cost-based comparison of quarantine strategies for new emerging diseases

A classical epidemiological framework is used to provide a preliminary cost analysis of the effects of quarantine and isolation on the dynamics of infectious diseases for which no treatment or immediate diagnosis tools are available. Within this framework we consider the cost incurred from the implementation of three types of dynamic control strategies. Taking the context of the 2003 SARS outbreak in Hong Kong as an example, we use a simple cost function to compare the total cost of each mixed (quarantine and isolation) control strategy from a public health resource allocation perspective. The goal is to extend existing epi-economics methodology by developing a theoretical framework of dynamic quarantine strategies aimed at emerging diseases, by drawing upon the large body of literature on the dynamics of infectious diseases. We find that the total cost decreases with increases in the quarantine rates past a critical value, regardless of the resource allocation strategy. In the case of a manageable outbreak resources must be used early to achieve the best results whereas in case of an unmanageable outbreak, a constant-effort strategy seems the best among our limited plausible sets.

Types of drinkers and drinking settings: an application of a mathematical model

AIMS US college drinking data and a simple population model of alcohol consumption are used to explore the impact of social and contextual parameters on the distribution of light, moderate and heavy drinkers. Light drinkers become moderate drinkers under social influence, moderate drinkers may change environments and become heavy drinkers. We estimate the drinking reproduction number, R(d) , the average number of individual transitions from light to moderate drinking that result from the introduction of a moderate drinker in a population of light drinkers. DESIGN AND SETTINGS Ways of assessing and ranking progression of drinking risks and data-driven definitions of high- and low-risk drinking environments are introduced. Uncertainty and sensitivity analyses, via a novel statistical approach, are conducted to assess R(d) variability and to analyze the role of context on drinking dynamics. FINDINGS Our estimates show R(d) well above the critical value of 1. R(d) estimates correlate positively with the proportion of time spent by moderate drinkers in high-risk drinking environments. R(d) is most sensitive to variations in local social mixing contact rates within low-risk environments. The parameterized model with college data suggests that high residence times of moderate drinkers in low-risk environments maintain heavy drinking. CONCLUSIONS With regard to alcohol consumption in US college students, drinking places, the connectivity (traffic) between drinking venues and the strength of socialization in local environments are important determinants in transitions between light, moderate and heavy drinking as well as in long-term prediction of the drinking dynamics.

Evaluating treatment of hepatitis C for hemolytic anemia management.

The combination therapy of antiviral peg-interferon and ribavirin has evolved as one of the better treatments for hepatitis C. In spite of its success in controlling hepatitis C infection, it has also been associated with treatment-related adverse side effects. The most common and life threatening among them is hemolytic anemia, necessitating dose reduction or therapy cessation. The presence of this side effect leads to a trade-off between continuing the treatment and exacerbating the side effects versus decreasing dosage to relieve severe side effects while allowing the disease to progress. The drug epoietin (epoetin) is often administered to stimulate the production of red blood cells (RBC) in the bone marrow, in order to allow treatment without anemia. This paper uses mathematical models to study the effect of combination therapy in light of anemia. In order to achieve this we introduce RBC concentration and amount of drug in the body as state variables in the usual immunological virus infection model. Analysis of this model provides a quantification of the amount of drug a body can tolerate without succumbing to hemolytic anemia. Indirect estimation of parameters allow us to calculate the necessary increment in RBC production to be > or =2.3 times the patients original RBC production rate to sustain the entire course of treatment without encountering anemia in a sensitive patient.

Some models for epidemics of vector-transmitted diseases

Vector-transmitted diseases such as dengue fever and chikungunya have been spreading rapidly in many parts of the world. The Zika virus has been known since 1947 and invaded South America in 2013. It can be transmitted not only by (mosquito) vectors but also directly through sexual contact. Zika has developed into a serious global health problem because, while most cases are asymptomatic or very light, babies born to Zika - infected mothers may develop microcephaly and other very serious birth defects. We formulate and analyze two epidemic models for vector-transmitted diseases, one appropriate for dengue and chikungunya fever outbreaks and one that includes direct transmission appropriate for Zika virus outbreaks. This is especially important because the Zika virus is the first example of a disease that can be spread both indirectly through a vector and directly (through sexual contact). In both cases, we obtain expressions for the basic reproduction number and show how to use the initial exponential growth rate to estimate the basic reproduction number. However, for the model that includes direct transmission some additional data would be needed to identify the fraction of cases transmitted directly. Data for the 2015 Zika virus outbreak in Barranquilla, Colombia has been used to fit parameters to the model developed here and to estimate the basic reproduction number.

Contextual Interventions for Controlling Alcohol Drinking

The dynamics of an alcohol drinking population are subject to environment-specific control programs. The stochastic model is developed that includes populations of light, moderate, and heavy drinkers, interacting in two contrasting risk-level drinking environments. For colleges with serious drinking problems, the times to disappearance of serious drinkers show that environment-dependent control programs have lasting efficacy when they are implemented according to the risk level of the environments and not by simply focusing on heavy drinking.

Impact of socio-economic conditions on the incidence of visceral leishmaniasis in Bihar, India

Visceral leishmaniasis (VL) is one of the worlds worst parasitic killers, second only to Malaria, claiming thousands of lives every year. More than three fifths of the worlds VL cases occur in the Indian state of Bihar alone. While some research has been conducted with emphasis on the effects of climatic variables on the VL incidence rate, rigorous analysis of the effects of socio-economic variables is still lacking. In this paper a regression model is developed that describes the relationship between VL incidence rate and a variety of socio-economic factors. It uses data from 2005 and explains 92% of the observed variance. In addition, a stepwise regression model is also used to identify the most important factors that facilitate the prevalence of the VL disease. A discussion on how to most effectively distribute Bihars limited resources on various control measures to decrease the incidence of VL is also presented.